6db2596ca9
Attempting to fix issues pointed out by Vadim Pisarevsky during the pull request review. In particular, the following things are done: *) The mechanism of debug info printing is changed and made more procedure-style than the previous macro-style *) z in solveLP() is now returned as a column-vector *) Func parameter of solveLP() is now allowed to be column-vector, in which case it is understood to be the transpose of what we need *) Func and Constr now can contain floats, not only doubles (in the former case the conversion is done via convertTo()) *)different constructor to allocate space for z in solveLP() is used, making the size of z more explicit (this is just a notation change, not functional, both constructors are achieving the same goal) *) (big) mat.hpp and iostream headers are moved to precomp-headers from optim.hpp
115 lines
3.3 KiB
C++
115 lines
3.3 KiB
C++
#include "test_precomp.hpp"
|
|
#include <iostream>
|
|
|
|
TEST(Optim_LpSolver, regression_basic){
|
|
cv::Mat A,B,z,etalon_z;
|
|
|
|
if(true){
|
|
//cormen's example #1
|
|
A=(cv::Mat_<double>(3,1)<<3,1,2);
|
|
B=(cv::Mat_<double>(3,4)<<1,1,3,30,2,2,5,24,4,1,2,36);
|
|
std::cout<<"here A goes\n"<<A<<"\n";
|
|
cv::optim::solveLP(A,B,z);
|
|
std::cout<<"here z goes\n"<<z<<"\n";
|
|
etalon_z=(cv::Mat_<double>(3,1)<<8,4,0);
|
|
ASSERT_EQ(cv::countNonZero(z!=etalon_z),0);
|
|
}
|
|
|
|
if(true){
|
|
//cormen's example #2
|
|
A=(cv::Mat_<double>(1,2)<<18,12.5);
|
|
B=(cv::Mat_<double>(3,3)<<1,1,20,1,0,20,0,1,16);
|
|
std::cout<<"here A goes\n"<<A<<"\n";
|
|
cv::optim::solveLP(A,B,z);
|
|
std::cout<<"here z goes\n"<<z<<"\n";
|
|
etalon_z=(cv::Mat_<double>(2,1)<<20,0);
|
|
ASSERT_EQ(cv::countNonZero(z!=etalon_z),0);
|
|
}
|
|
|
|
if(true){
|
|
//cormen's example #3
|
|
A=(cv::Mat_<double>(1,2)<<5,-3);
|
|
B=(cv::Mat_<double>(2,3)<<1,-1,1,2,1,2);
|
|
std::cout<<"here A goes\n"<<A<<"\n";
|
|
cv::optim::solveLP(A,B,z);
|
|
std::cout<<"here z goes\n"<<z<<"\n";
|
|
etalon_z=(cv::Mat_<double>(2,1)<<1,0);
|
|
ASSERT_EQ(cv::countNonZero(z!=etalon_z),0);
|
|
}
|
|
}
|
|
|
|
TEST(Optim_LpSolver, regression_init_unfeasible){
|
|
cv::Mat A,B,z,etalon_z;
|
|
|
|
if(true){
|
|
//cormen's example #4 - unfeasible
|
|
A=(cv::Mat_<double>(1,3)<<-1,-1,-1);
|
|
B=(cv::Mat_<double>(2,4)<<-2,-7.5,-3,-10000,-20,-5,-10,-30000);
|
|
std::cout<<"here A goes\n"<<A<<"\n";
|
|
cv::optim::solveLP(A,B,z);
|
|
std::cout<<"here z goes\n"<<z<<"\n";
|
|
etalon_z=(cv::Mat_<double>(3,1)<<1250,1000,0);
|
|
ASSERT_EQ(cv::countNonZero(z!=etalon_z),0);
|
|
}
|
|
}
|
|
|
|
TEST(Optim_LpSolver, regression_absolutely_unfeasible){
|
|
cv::Mat A,B,z,etalon_z;
|
|
|
|
if(true){
|
|
//trivial absolutely unfeasible example
|
|
A=(cv::Mat_<double>(1,1)<<1);
|
|
B=(cv::Mat_<double>(2,2)<<1,-1);
|
|
std::cout<<"here A goes\n"<<A<<"\n";
|
|
int res=cv::optim::solveLP(A,B,z);
|
|
ASSERT_EQ(res,-1);
|
|
}
|
|
}
|
|
|
|
TEST(Optim_LpSolver, regression_multiple_solutions){
|
|
cv::Mat A,B,z,etalon_z;
|
|
|
|
if(true){
|
|
//trivial example with multiple solutions
|
|
A=(cv::Mat_<double>(2,1)<<1,1);
|
|
B=(cv::Mat_<double>(1,3)<<1,1,1);
|
|
std::cout<<"here A goes\n"<<A<<"\n";
|
|
int res=cv::optim::solveLP(A,B,z);
|
|
printf("res=%d\n",res);
|
|
printf("scalar %g\n",z.dot(A));
|
|
std::cout<<"here z goes\n"<<z<<"\n";
|
|
ASSERT_EQ(res,1);
|
|
ASSERT_EQ(z.dot(A),1);
|
|
}
|
|
|
|
if(false){
|
|
//cormen's example from chapter about initialize_simplex
|
|
//online solver told it has inf many solutions, but I'm not sure
|
|
A=(cv::Mat_<double>(2,1)<<2,-1);
|
|
B=(cv::Mat_<double>(2,3)<<2,-1,2,1,-5,-4);
|
|
std::cout<<"here A goes\n"<<A<<"\n";
|
|
int res=cv::optim::solveLP(A,B,z);
|
|
printf("res=%d\n",res);
|
|
printf("scalar %g\n",z.dot(A));
|
|
std::cout<<"here z goes\n"<<z<<"\n";
|
|
ASSERT_EQ(res,1);
|
|
}
|
|
}
|
|
|
|
TEST(Optim_LpSolver, regression_cycling){
|
|
cv::Mat A,B,z,etalon_z;
|
|
|
|
if(true){
|
|
//example with cycling from http://people.orie.cornell.edu/miketodd/or630/SimplexCyclingExample.pdf
|
|
A=(cv::Mat_<double>(4,1)<<10,-57,-9,-24);
|
|
B=(cv::Mat_<double>(3,5)<<0.5,-5.5,-2.5,9,0,0.5,-1.5,-0.5,1,0,1,0,0,0,1);
|
|
std::cout<<"here A goes\n"<<A<<"\n";
|
|
int res=cv::optim::solveLP(A,B,z);
|
|
printf("res=%d\n",res);
|
|
printf("scalar %g\n",z.dot(A));
|
|
std::cout<<"here z goes\n"<<z<<"\n";
|
|
ASSERT_EQ(z.dot(A),1);
|
|
//ASSERT_EQ(res,1);
|
|
}
|
|
}
|